As an interpretation of existing jamming effects, the main variables affecting the increase in stiffness due to jamming are known as system density, jamming density, pressure, and particulate temperature. The main variable, jamming density, is closely related to the distribution of particle size and contact properties such as particle shape and friction. However, the complexity of these variables makes it difficult to fully understand the mechanism of the jamming effect. In this paper, we focus on the jamming effects of particles that have more elastic properties than particles such as sand and coffee powder, which are commonly used as constituent particles of existing jamming, in order to reduce complicated factors such as temperature and concentrate on jamming effects based on elastic characteristics of particles. It was experimentally explored the possibility of increasing stiffness by mixing particles of different sizes rather than simply increasing the bending stiffness by controlling the particle size. Through simulations and experiments, we found a case where the stiffness of each particle size distribution is larger than the stiffness of each particle size.

In this paper, we propose a new collision detection algorithm for human-robot collaboration. We use an IMU sensor located at the tip of the manipulator and the kinematic behavior of the manipulator to detect the unexpected collision between the robotic manipulator and environment. Unlike other method, the developed algorithm uses only the kinematic relationship between the manipulator joint and the end effector. Therefore, the collision estimation signal is not affected by the error of the dynamics model. The proposed collision detection algorithm detects the collision by comparing the estimated acceleration of the end effector derived from the position, velocity and acceleration trajectories of the robot joints with the actual acceleration measured by the sensor. In simulation, we compare the performance of our method with the conventional Residual Observer (ROB). Our method is less sensitive to the load variation because of the independency on the dynamic modeling of the manipulator.

A design methodology for parametric design optimization of washing machine door is presented. We develop a motion simulator and a robotic door to simulate the various motion of washing machine doors. The motion of the washing machine door is related to hinge parameters. Springs and dampers are usually used in the hinge of washing machine door for controlling motion of the door. A physical simulator of the door motion is used for finding candidate parameters of the hinge and a robotic door whose motion is controlled algorithmically is used for consumer tests. Through the consumer evaluation on the robotic motion, the optimized parameters are determined. We find the optimal parameters as a function of angle and angular velocity of the door.

To realize a robot hand interacting like a human hand, there are many tactile sensors sensing normal force, shear force, torque, shape, roughness and temperature. This sensing signal is essential to manipulate object accurately with robot hand. In particular, slip sensors make manipulation more accurate and breakless to object. Up to now several slip sensors were developed and applied to robot hand. Many of them used complicate algorithm and signal processing with vibration data. In this paper, we developed novel principle slip sensor using separation layer. These two layers are moved from each other when slip occur. Developed sensor can sense slip signal by measuring this relative displacement between two layers. Also our principle makes slip signal decoupled from normal force and shear force without other sensors. The sensor was fabricated using the NBR(acrylo-nitrile butadiene rubber) and the Ecoflex as substrate and a paper as dielectric. To verify our sensor, slip experiment and normal force decoupling test were conducted.

Mapping is a fundamental element for robotic services. There are available many types of map data representation such as grid map, metric map, topology map, etc. As more robots are deployed for services, more chances of exchanging map data among the robots emerge and standardization of map data representation (MDR) becomes more valuable. Currently, activities in developing MDR standard are underway in IEEE Robotics and Automation Society. The MDR standard is for a common representation and encoding of the two-dimensional map data used for navigation by mobile robots. The standard focuses on interchange of map data among components and systems, particularly those that may be supplied by different vendors. This paper aims to introduce MDR standard and its application to map merging. We have applied the basic structure of the MDR standard to a grid map and Voronoi graph as a kind of topology map and performed map merging between two different maps. Simulation results show that the proposed MDR is suitable for map data exchange among robots.

In this paper, we introduce an internal pipeline exploration of an in-pipe robot, based on the landmark recognition system. The fittings of pipelines such as elbows and branches are used as the landmarks. The robot recognizes the landmarks with a vision system by using the shadows of the elements, which are generated by the specially designed illuminator on the robot. By using a simple image-processing, the robot can easily detect and distinguish these landmarks while recognizing the direction of the pipeline path. Simultaneously, all information for exploration is continuously recorded and used to reconstruct the map of the pipelines. The effectiveness of the proposed method is verified by real experiments using the in-pipe robot MRINSPECT V for moving inside of the miniature urban 8-inch gas pipeline structure.

In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of xe, ye, θe correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.

In this paper, a wall climbing robot, called LAVAR, is developed, which is using an impeller for adhering. The adhesion mechanism of the robot consists of an impeller and two-layered suction seals which provide sufficient adhesion force for the robot body on the non smooth vertical wall and horizontal ceiling. The robot uses two driving-wheels and one ball-caster to maneuver the wall surface. A suspension mechanism is also used to overcome the obstacles on the wall surface. For its design, the whole adhering mechanism is analyzed and the control system is built up based on this analysis. The performances of the robot are experimentally verified on the vertical and horizontal flat surfaces.

In this study, an anthropomorphic robot Hand, called “SKKU Hand III” is presented. The hand has thirteen DOF(Degree-Of-Freedom) and is designed based on the skeletal structure of the human hand. Each finger module(except thumb module) has three DOF and four joints with a saddle joint mechanism which has two DOF at the base joint. Two distal joints of the finger module are mechanically coupled by a timing belt and pulleys. The thumb module is composed of a finger module and an additional actuator, which makes it possible to realize the opposition between the thumb and the other fingers. In addition, the palm DOF of the human hand is mimicked with a spatial link mechanism between the index finger and the thumb. Thus, it can grasp objects more stably and more strongly. For the modularization of the robotic hand all the driving circuits are embedded in the hand, and only the communication lines supporting CAN protocol with DC power cable are given as an interface. Therefore, it is possible to apply it to any robot system the interface. To validate the feasibility of the SKKU Hand III, a series of the representative grasp experiments such as power, precision, intermediate grasp etc. are carried out with the object around us and its operation is demonstrated.

Recently researches on the window cleaning robot are being conducted actively. Moving mechanisms of these window cleaning robots are divided into two categories, which are towed type and walking type. Towed type is focused on fast cleaning on the flat surface of building and walking type has priority on cleaning task on relatively complex surface with overcoming obstacles. Currently commercialized towed type window cleaning robot has weakness that it is hard to adhere closely with the wall and easy to be affected by wind. In case of walking type it has the problem that the position errors are continuously accumulated during motion. In this paper, we propose new towed and walking type mechanism which can compensate previous weaknesses. After that we estimate the performance of each proposed mechanism by simulation.